Department of Computer Science, University of Texas at El Paso
Abstract: Potential applicants to graduate school find it difficult to predict, even approximately, which schools will accept them. We have created a predictive model of admissions decision-making, packaged in the form of a web page that allows students to enter their information and see a list of schools where they are likely to be accepted. This paper explains the rationale for the model's design and parameter values. Interesting issues include the way that evidence is combined, the estimation of parameters, and the modeling of uncertainty.
Keywords: student assessment, acceptance criteria, decision-making, combination of evidence, ordered weighted average
Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.10, No.3, pp. 372-383, 2006.
Full Paper, as published (at Fuji Press)
Full Paper, late draft
Acceptance Estimator for CS Graduate Admissions